Towards quantum 3D imaging devices: the Qu3D project

TL;DR

This paper reviews the development of quantum plenoptic cameras that leverage quantum entanglement and correlations to achieve superior 3D imaging capabilities, including diffraction-limited resolution and large depth of focus, while addressing practical challenges.

Contribution

It introduces novel quantum 3D imaging devices based on entanglement, proposes protocols to surpass diffraction limits, and develops advanced hardware and algorithms to reduce data acquisition and processing times.

Findings

Quantum plenoptic cameras achieve diffraction-limited resolution.

Development of high-resolution SPAD arrays improves data acquisition.

Algorithms reduce data processing time by two orders of magnitude.

Abstract

We review the advancement of the research toward the design and implementation of quantum plenoptic cameras, radically novel 3D imaging devices that exploit both momentum-position entanglement and photon-number correlations to provide the typical refocusing and ultra-fast, scanning-free, 3D imaging capability of plenoptic devices, along with dramatically enhanced performances, unattainable in standard plenoptic cameras: diffraction-limited resolution, large depth of focus, and ultra-low noise. To further increase the volumetric resolution beyond the Rayleigh diffraction limit, and achieve the quantum limit, we are also developing dedicated protocols based on quantum Fisher information. However, for the quantum advantages of the proposed devices to be effective and appealing to end-users, two main challenges need to be tackled. First, due to the large number of frames required for correlation measurements to provide an acceptable SNR, quantum plenoptic imaging would require, if implemented with commercially available high-resolution cameras, acquisition times ranging from tens of seconds to a few minutes. Second, the elaboration of this large amount of data, in order to retrieve 3D images or refocusing 2D images, requires high-performance and time-consuming computation. To address these challenges, we are developing high-resolution SPAD arrays and high-performance low-level programming of ultra-fast electronics, combined with compressive sensing and quantum tomography algorithms, with the aim to reduce both the acquisition and the elaboration time by two orders of magnitude. Routes toward exploitation of the QPI devices will also be discussed.